Model Risk Program Analyst

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Corporate Sector

This role focuses on model validation and governance within JPMorgan Chase's Risk Management and Compliance organization. The analyst will evaluate the conceptual soundness, assumptions, inputs, testing, numerical robustness, and performance metrics of various models used in financial forecasting and business decisions. The role requires strong quantitative skills, experience with statistical/econometric models, proficiency in Python/R, and a deep understanding of financial products and regulatory stress testing.

What you'd actually do

  1. Engage in typical model validation activities, including evaluating the conceptual soundness of model specifications, the reasonableness of assumptions and reliability of inputs, the completeness of testing performed to support the correctness of the implementation, the robustness of numerical aspects, and the suitability and comprehensiveness of performance metrics and risk measures associated with the use of the models.
  2. Perform additional model review activities, including proposing enhancements to existing models, assessing extensions to the scope of existing models, and developing benchmarking models.
  3. Apply in-depth understanding of the drivers of balances and revenues for different investment banking and Markets products and businesses by using a combination of research and liaising with business lines.
  4. Liaise with Risk and Finance professionals to provide oversight and guidance on appropriate usage, controls around model restrictions and limitations, and findings for ongoing performance assessment and testing.
  5. Maintain model risk control apparatus of the bank for the coverage area and serve as the first point of contact.

Skills

Required

  • Master's degree in a quantitative field (Math, Physics, Engineering, Statistics, Economics or Finance)
  • 0-2 years of experience in a quantitative or modeling role
  • Deep understanding of statistical/econometric models (linear, logistics, time series)
  • Proficiency in Python, R, or equivalent
  • Strong communication skills (verbal and written)
  • Risk and control mindset

Nice to have

  • Domain expertise in PPNR and balance sheet modeling, stress testing exercises (such as CCAR, ICAAP, etc.), financial forecasting, econometrics and statistics, and machine learning methods
  • Prior experience in financial products/markets and regulatory stress testing (CCAR/ICAAP)

What the JD emphasized

  • model validation
  • model governance
  • quantitative field
  • quantitative or modeling role
  • statistical/econometric models
  • Python, R
  • PPNR and balance sheet modeling
  • stress testing exercises
  • financial forecasting
  • econometrics and statistics
  • machine learning methods
  • model-related issues
  • model risk control
  • regulatory stress testing